Recent trends have shown that there are more and more applications, or apps, created to fulfill users' tasks. Many of these apps are available at online locations, such as retail websites, in order to offer users an effortless app-shopping experience that may be customized for devices and/or scenarios. For example, various platforms (e.g., Apple®, Android®, and Microsoft®) have had exponential growth in their respective app stores and currently offer over 500,000 aggregate apps for their respective mobile devices. One such exemplary web-centric application is the Yelp® app—the counterpart application to the www.yelp.com website—that is customized to be installed on a variety of mobile devices.
Yet, along with this ever-expanding multitude of apps, there exists a discoverability problem. That is, popular or relevant applications are often hard to discover via online searches. This discoverability problem stems from the standard search protocol of conventional search engines, which surface mainly websites, cards, and answers. This is true for both desktop and mobile devices.
Some search-engine technology provides rudimentary mechanism(s) that allow a user to find applications if an application-index web page (e.g., app store) is being specifically queried by a user via a search engine. Or, there may exist mechanisms can return applications if a user-request is explicitly seeking an app (e.g., “download Yelp® app”). However, when a user-initiated query or request does not explicitly point to applications, the conventional search engines simply return links to websites without consideration of relevant apps. For example, when a user queries “Italian restaurants Bellevue reservation,” conventional search engines typically return a number of websites of businesses local to Bellevue, Wash., that serve or cater Italian food. While these search results are generally acceptable, the conventional search engines fall short of entirely satisfying a user's searching intent by failing to discover and present those applications that might help the user more efficiently complete their task(s) underlying the searching intent.